Engineering, Electrical and Electronic Engineering, Insect Science
34
Scopus Publications
376
Scholar Citations
9
Scholar h-index
9
Scholar i10-index
Scopus Publications
Novel energy efficient RND inverter using quantum dot cellular automata in nanotechnology Madhavi Repe, Sanjay Koli Scientific Reports, 2024 Quantum-Dot Cellular Automata (QCA) is a promising technology for designing high-performance and efficient logic circuits, surpassing traditional Complementary Metal Oxide Semiconductor approaches. In today’s digital era, the demand for digital circuits with high speed, device density, and energy efficiency is paramount. This paper focuses on the innovative Rotated Normal Cells with Displacement (RND) inverter model, employing normal and rotated cells with a 10 nm displacement through a cell interactive method. Digital circuits designed using the RND inverter exhibit superior performance compared to existing designs. The proposed RND inverter gate utilizes only four QCA cells, occupying a total area of 4525.55 nm2. With a total energy dissipation of 0.508 meV and an average energy dissipation per cycle of 0.0462 meV, it achieves a polarization of 9.77. The novel RND inverter demonstrates a 44% improvement in cell area and a 63% reduction in total area compared to current designs, offering enhanced energy efficiency with 0.26 improved polarization. The RND inverter and the digital circuits facilitate finding applications in efficiently constructing various components within Quantum Computers. Beyond quantum computing, the RND inverter proves applicable in designing Nano-sized electronic gadgets and temperature-controlled circuits, showcasing its versatility across diverse technological applications.
Enhanced deep learning technique for sugarcane leaf disease classification and mobile application integration Swapnil Dadabhau Daphal, Sanjay M. Koli Heliyon, 2024 With an emphasis on classifying diseases of sugarcane leaves, this research suggests an attention-based multilevel deep learning architecture for reliably classifying plant diseases. The suggested architecture comprises spatial and channel attention for saliency detection and blends features from lower to higher levels. On a self-created database, the model outperformed cutting-edge models like VGG19, ResNet50, XceptionNet, and EfficientNet_B7 with an accuracy of 86.53%. The findings show how essential all-level characteristics are for categorizing images and how they can improve efficiency even with tiny databases. The suggested architecture has the potential to support the early detection and diagnosis of plant diseases, enabling fast crop damage mitigation. Additionally, the implementation of the proposed AMRCNN model in the Android phone-based application gives an opportunity for the widespread use of mobile phones in the classification of sugarcane diseases.
Optimized Vedic Multiplier Using 3nm Nanosheet Technology Swati S. Shetkar, Sanjay Koli 2024 International Conference on Emerging Smart Computing and Informatics Esci 2024, 2024 Nanosheet FET technology is an alternative to FinFET and CMOS technology as it gives low leakage current and low power consumption. NS-FET has better mobility and scaling compared to CMOS technology. Multiplier is an important arithmetic circuit required in many digital arithmetic applications. Area, power-efficient multiplier is the need of ALU. Vedic sutras not only reduce hardware but also improve parameters like power and delay. This paper explains the implementation of Vedic arithmetic circuits of 3 nm NS-FET technology in physical layout. The proposed designs are implemented in Micro wind EDA 3.9 with 3 nm deep submicron technology post layout. The values of model parameters are used from the current Berkeley 4 short channel model (BSIM-CMG). The performances of the Ex-OR gate, 2-bit Vedic multiplier are analyzed. Analyzed results show that the proposed I design of Vedic Multiplier shows 96.40% and the proposed II design shows 117.82% power reduction compared to the 14nm VM.
Squaring Circuit Using 14nmFinFET Technology with Vedic Mathematics Approach Swati Shetkar, Sanjay Koli IETE Journal of Research, 2024 FinFET technology is an alternative to CMOS technology as in this technology device has higher drive current, speed, and low-power consumption. FinFET has better mobility and scaling than CMOS technology. A dedicated Squaring circuit is needed by many digital signal processors (DSP) and arithmetic and logical units (ALU). So fast, power-efficient, and compact squaring circuits can be designed with Vedic sutras. Vedic mathematics has 16 sutras and 13 sub-sutras that touch almost all different chapters of mathematics. Out of these sutras, Dwandwayoga has a duplex property that is used to find a square of an N-bit number. Also, Yavadunam is a special case for finding the square of a number that is closer to the base. This work targets a comparative analysis of these two square circuits having a Vedic approach with a conventional array multiplier. The proposed designs are implemented in micro-wind 3.9 electronic design automation tool (EDA) with 14 nm deep submicron technology post-layout. The values of model parameters are used from the current Berkeley 4 short channel model (BSIM4). It is observed that the proposed square architecture design using the Dwandwayog sutra and Yavadunam sutra achieves 185%, 272.45% delay depletion and a 122.22%, and 46.52% reduction in transistor requirements compared to the conventional array multiplier, respectively.
Enhancing sugarcane disease classification with ensemble deep learning: A comparative study with transfer learning techniques Swapnil Dadabhau Daphal, Sanjay M. Koli Heliyon, 2023 Deep learning practices in the agriculture sector can address many challenges faced by the farmers such as disease detection, yield estimation, soil profile estimation, etc. In this paper, disease classification for the sugarcane plant and the experimentation involved thereby is thoroughly discussed. Experimental results include the performances of the well-known existing transfer learning techniques and proposed ensemble deep learning based architecture that incorporates stack ensemble of two networks with one having level-wise spatial attention helping to provide better generalization. A Self-created database of sugarcane leaf diseases is introduced to the research community through this paper. It involves 5 categories with a total of 2569 images. Here, it is observed that best performing transfer learning method, MobileNet-V2 shows an accuracy of around 84% with the lowest number of parameters whereas ensemble model reaching to 86.53% with less epochs and with acceptable number of parameters.
Flip Flops Design in Quantum Dot Cellular Automata Technology: Towards Digitization Madhavi Repe, Sanjay Koli International Journal on Recent and Innovation Trends in Computing and Communication, 2023 Quantum-Dot Cellular Automata (QCA) is a transistor-less technology. In QCA, Columbic repulsion between electrons in the quantum dots makes data transfer possible. This paper presents the design of flip flops using a proposed Rotated-Normal Cells with Displacement (RND) inverter and a cell interaction method. The SR latch, SR Flip Flop (FF), D FF, and T FF are developed using QCA. The proposed D FF gives total and average energy dissipation of 1.31e-002eV and 1.19e-003eV respectively. It also gives a delay of 1 clock phase. The Proposed T FF provides total and average energy dissipation of 2.40e-002eV and 2.18e-003eV respectively, depicting efficient D FF and T FF in energy dissipation. The proposed SR Flip flop design gives an efficient area. The FFs with the proposed RND inverter and cell interaction method can be the best choice for future Nano communication to construct Nano circuits with less energy dissipation and high speed.
A Solution to VLSI: Digital Circuits Design in Quantum Dot Cellular Automata Technology Madhavi Repe, Sanjay Koli International Journal of Electrical and Electronics Research, 2023 Quantum Dot Cellular Automata is a Nano device efficient than other devices in nanotechnology for the last two decades. It is beneficial over Complementary Metal Oxide Semiconductor technology like high speed, low energy dissipation, high device density and high computation efficiency. To achieve further optimization different methods like simplifications in Boolean expressions, tile method, clocking scheme, cell placement, cell arrangement, novel input techniques, etc., are in use. These methods improve the performance metrics in terms of QCA Cells, total circuit area, delay in output, power consumption, and coplanar or multilayer layout. This paper is about the novel NOT gate layout designed with efficient parameters compared to existing NOT gates except area parameters with analysis and XOR gate and multiplexer circuits. The novel gate provides an improvement of 55% in the number of cells, polarization raised by 0.33, and an 80.77% improvement in total area. These circuits illustrate further scope in QCA circuit design efficiently. XOR circuit shows area reduction up to 0.006 μm2 with 0.5 clock cycle delay. Further optimization in XOR parameters and with this novel NOT gate researchers can optimize parameters to bring revolution and digitalization.
Squaring Circuit Using 14nmFinFET Technology with Vedic Mathematics Approach S Shetkar, S Koli IETE Journal of Research 70 (10), 7980-7988 , 2024 2024 Citations: 1
Enhanced deep learning technique for sugarcane leaf disease classification and mobile application integration SD Daphal, SM Koli Heliyon 10 (8) , 2024 2024 Citations: 64
Optimized Vedic Multiplier Using 3nm Nanosheet Technology SS Shetkar, S Koli 2024 International Conference on Emerging Smart Computing and Informatics … , 2024 2024 Citations: 1
Enhanced Classification of Sugarcane Diseases Through a Modified Learning Rate Policy in Deep Learning. SD Daphal, SM Koli Traitement du Signal 41 (1) , 2024 2024 Citations: 11
Novel energy efficient RND inverter using quantum dot cellular automata in nanotechnology M Repe, S Koli Scientific Reports 14 (1), 190 , 2024 2024 Citations: 7
Enhanced deep learning technique for sugarcane leaf disease classification and mobile application integration. Heliyon 10 (8): e29438 SD Daphal, SM Koli 2024 Citations: 12
Area, power efficient Vedic multiplier architecture using novel 4: 2 compressor S Shetkar, S Koli Sādhanā 48 (4), 216 , 2023 2023 Citations: 11
A Solution to VLSI: Digital Circuits Design in Quantum Dot Cellular Automata Technology M Repe, S Koli International Journal of Electrical and Electronics Research 11 (3), 696-704 , 2023 2023 Citations: 1
Enhancing sugarcane disease classification with ensemble deep learning: A comparative study with transfer learning techniques SD Daphal, SM Koli Heliyon 9 (8) , 2023 2023 Citations: 79
Flip Flops Design in Quantum Dot Cellular Automata Technology: Towards Digitization M Repe International Journal on Recent and Innovation Trends in Computing and … , 2023 2023 Citations: 2
FabDepth I: a unique dataset for efficient gesture detection R Shamalik, S Koli International Journal of Information Technology 15 (5), 2645-2649 , 2023 2023 Citations: 2
Effective and efficient approach for gesture detection in video through monocular RGB frames R Shamalik, S Koli Multimedia Tools and Applications 82 (11), 17231-17242 , 2023 2023 Citations: 2
Enhancing sugarcane disease classification with ensemble deep learning: a comparative study with transfer learning techniques. Heliyon 9 (8): e18261 SD Daphal, SM Koli 2023 Citations: 6
DeepHands: Dynamic hand gesture detection with depth estimation and 3D reconstruction from monocular RGB data R Shamalik, S Koli Sādhanā 47 (4), 247 , 2022 2022 Citations: 4
Real Time Gesture Detection Using Convolutional Neural Network R Shamalik, S Koli 2022 IEEE 4th International Conference on Cybernetics, Cognition and Machine … , 2022 2022
Compact D Flip Flop in Quantum Dot Cellular Automata for Digital System MR Repe, S Koli 2022 6th International Conference On Computing, Communication, Control And … , 2022 2022
Design methods in nanotechnology using quantum dot cellular automata (QCA) M Repe, S Koli 2022 2nd International Conference on Intelligent Technologies (CONIT), 1-5 , 2022 2022 Citations: 1
Single Shot Detector for Multi-vehicle Detection and Tracking in Different Lighting and Weather Conditions S Jahagirdar, S Koli ICCCE 2021: Proceedings of the 4th International Conference on … , 2022 2022 Citations: 2
Efficient use of convolutional neural networks for classification of sugarcane leaf diseases SD Daphal, SM Koli ICCCE 2021: Proceedings of the 4th International Conference on … , 2022 2022 Citations: 4
Sugarcane leaf disease dataset. mendeley data, v1 S Daphal, S Koli 2022 Citations: 5
MOST CITED SCHOLAR PUBLICATIONS
Enhancing sugarcane disease classification with ensemble deep learning: A comparative study with transfer learning techniques SD Daphal, SM Koli Heliyon 9 (8) , 2023 2023 Citations: 79
Enhanced deep learning technique for sugarcane leaf disease classification and mobile application integration SD Daphal, SM Koli Heliyon 10 (8) , 2024 2024 Citations: 64
Sugarcane leaf disease dataset S Daphal, S Koli Mendeley Data 1 , 2022 2022 Citations: 25
Transfer Learning approach to Sugarcane Foliar disease Classification with state-of-the-art Sugarcane Database SD Daphal, SM Koli 2021 International Conference on Computational Intelligence and Computing … , 2021 2021 Citations: 21
Enhanced deep learning technique for sugarcane leaf disease classification and mobile application integration. Heliyon 10 (8): e29438 SD Daphal, SM Koli 2024 Citations: 12
Analysis of various parameters for link adaptation in wireless transmission RG Purandare, SP Kshirsagar, SM Koli Innovations in Computer Science and Engineering: Proceedings of the Third … , 2016 2016 Citations: 12
Enhanced Classification of Sugarcane Diseases Through a Modified Learning Rate Policy in Deep Learning. SD Daphal, SM Koli Traitement du Signal 41 (1) , 2024 2024 Citations: 11
Area, power efficient Vedic multiplier architecture using novel 4: 2 compressor S Shetkar, S Koli Sādhanā 48 (4), 216 , 2023 2023 Citations: 11
Automatic Accident Detection Techniques using CCTV Surveillance Videos: Methods, Data Sets and Learning Strategies S Jahagirdar, S Koli International Journal of Engineering and Advanced Technology (IJEAT) 9 (3 … , 2020 2020 Citations: 10
Impact of bit error on video transmission over wireless networks and error resiliency RG Purandare, SP Kshirsagar, SM Koli, VV Gohokar 2011 International Conference on Image Information Processing, 1-6 , 2011 2011 Citations: 9
Identification of Sugarcane Foliar Diseases: Methods and Datasets SD Daphal, SM Koli International Journal of Engineering and Advanced Technology (IJEAT) 9 (3 … , 2020 2020 Citations: 8
A survey on video transmission using wireless technology SM Koli, RG Purandare, SP Kshirsagar, VV Gohokar International Conference on Computer Science and Information Technology, 137-147 , 2011 2011 Citations: 8
Novel energy efficient RND inverter using quantum dot cellular automata in nanotechnology M Repe, S Koli Scientific Reports 14 (1), 190 , 2024 2024 Citations: 7
Enhancing sugarcane disease classification with ensemble deep learning: a comparative study with transfer learning techniques. Heliyon 9 (8): e18261 SD Daphal, SM Koli 2023 Citations: 6
Loss differentiated channel aware rate adaptation for IEEE 802.11 n wireless links RG Purandare, SP Kshirsagar, SM Koli Wireless Personal Communications 107 (4), 2211-2230 , 2019 2019 Citations: 6
Weather Prediction using Multiple IoT Based Wireless Sensors S Heeralal, Kumar, K S, M Acta Technica Corviniensis-Bulletin of Engineering, Romania 12 (4), 123-127 , 2019 2019 Citations: 6
Raspberry pi based reader for blind MS Jadhav, MSM Koli, MSS Kulkarni, MSMSS Akhtar, MHD Ingle Int. J. Innov. Emerg. Res. Eng 5 (1), 1639-1642 , 2018 2018 Citations: 6
Sugarcane leaf disease dataset. mendeley data, v1 S Daphal, S Koli 2022 Citations: 5
Real time human gesture recognition: methods, datasets and strategies R Shamalik, S Koli Recent trends in intensive computing, 251-255 , 2021 2021 Citations: 5
Transformation of video signal processing techniques from 2D to 3D: a survey S Koli, R Shamalik ICCCE 2019: Proceedings of the 2nd International Conference on … , 2019 2019 Citations: 5