Power-Aware ReRAM-Based Processing-in-Memory Architecture for Hyperdimensional Computing Using Clock Gating
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1SHEIK RIZWANA, 2GUTTULA VENKATARAMANA
Hyperdimensional Computing (HDC) is an emerging computing paradigm inspired by the human brain, where information is represented using high-dimensional vectors known as hyper vectors.
DOI:30.0485/ijearst.10.03.3493
1SHEIK RIZWANA, 2GUTTULA VENKATARAMANA
Hyperdimensional Computing (HDC) is an emerging computing paradigm inspired by the human brain, where information is represented using high-dimensional vectors known as hyper vectors.
DOI:30.0485/ijearst.10.03.3493
IoT-Enabled High Load Density Miniature Force Sensor System for Intelligent Robot Foot Probing and Obstacle Avoidance
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1Jampana Sushma 2Dr.R.V.V. Krishna
This project presents an enhanced version of a High Load Density Miniature Force Sensor for Probing with Robot Feet
DOI:30.0485/ijearst.10.03.3491
1Jampana Sushma 2Dr.R.V.V. Krishna
This project presents an enhanced version of a High Load Density Miniature Force Sensor for Probing with Robot Feet
DOI:30.0485/ijearst.10.03.3491
Power-efficient and Area-optimized Exposed Datapath Architecture Enhanced with a RISC-V Instruction Set
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1K. HEMANTH SURYA MANISAI, 2SATHIBABU MANDAPALLI
This project describes a 32-bit RISC microprocessor core that has been designed for portable applications.
DOI:30.0485/ijearst.10.01.3494
1K. HEMANTH SURYA MANISAI, 2SATHIBABU MANDAPALLI
This project describes a 32-bit RISC microprocessor core that has been designed for portable applications.
DOI:30.0485/ijearst.10.01.3494
High-Speed Approximate Hybrid Floating-Point Multiplication Using Radix-16 Modified Booth Encoding for Butter fly unit
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1CH.MANASA SATYA KUMARI, 2G.V. RAMANA
This project presents floating-point operations and applies them to the implementation of Butterfly unit.
30.0485/ijearst.10.01.3495
1CH.MANASA SATYA KUMARI, 2G.V. RAMANA
This project presents floating-point operations and applies them to the implementation of Butterfly unit.
30.0485/ijearst.10.01.3495
Medical Waste Classification using Deep Learning and Convolutional Neural Networks (TensorFlow)
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1VUTUKURI BALA VENKATA SAI, 2D. NAGA JYOTHI
This project focuses on developing an automated system for classifying medical waste using Deep Learning and Convolutional Neural Networks (CNNs).
30.0485/ijearst.10.01.3496
1VUTUKURI BALA VENKATA SAI, 2D. NAGA JYOTHI
This project focuses on developing an automated system for classifying medical waste using Deep Learning and Convolutional Neural Networks (CNNs).
30.0485/ijearst.10.01.3496
High-Performance ALU Architecture Using MGDI Based Logic Gates and Multiplexers
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1V. LAKSHMI TULASI, 2 V. RAVINDRA
This project presents the design of a low-power and area-efficient Arithmetic Logic Unit (ALU) using the Modified Gate Diffusion Input (MGDI) and Hybrid GDI design techniques.
30.0485/ijearst.10.01.3497
1V. LAKSHMI TULASI, 2 V. RAVINDRA
This project presents the design of a low-power and area-efficient Arithmetic Logic Unit (ALU) using the Modified Gate Diffusion Input (MGDI) and Hybrid GDI design techniques.
30.0485/ijearst.10.01.3497
Power and Density optimized Architecture for 3D Semantic Segmentation with Offset-Wise Weight Quantization using Radix8 booth encoding
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1Miriyala Ramalakshmi, 2N. Veera Durga
Three-dimensional (3D) semantic segmentation plays a vital role in modern applications such as autonomous driving,
30.0485/ijearst.10.01.3500
1Miriyala Ramalakshmi, 2N. Veera Durga
Three-dimensional (3D) semantic segmentation plays a vital role in modern applications such as autonomous driving,
30.0485/ijearst.10.01.3500
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