vansh-py04/Convolution-Net-from-Scratch

A minimal NumPy-based implementation of a 3-layer convolutional neural network (CNN) from scratch — including custom forward and backward passes for conv, ReLU, pooling, affine, and softmax layers. Perfect for learning how CNNs actually work under the hood.

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Shiritai/aias-lab6-spring-2024

Lab6 of AI computing Architecture and System (2024 spring) around riscv emulator and implementation of fibonacci, sudoku (2x2) and maxpool in RISC-V

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abrbird/NNNumpy

Neural networks

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GMfatcat/Go_C_filter

Test for the speed to do maxpooling in pure go , goroutine, and Cgo.

Language: Go - Size: 4.04 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

Adversarial-Intelligence-Group/flexnets

Hyper-Flexible Convolutional Neural Networks Based on Generalized Lehmer and Power Means

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Naveenad2/Deep-Learning-Driven-Leaf-Photo-Analysis-for-Plant-Disease-Prediction

Deep Learning-Driven Leaf Photo Analysis for Plant Disease Prediction is an innovative deep learning project that harnesses the power of Convolutional Neural Networks (CNNs) to revolutionize plant disease prediction.

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mdnuruzzamanKALLOL/CNN-Implementation_1

Basic_CNN_Implementation

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mdnuruzzamanKALLOL/CNN_Basic

CNN

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Najib-Haq/Vectorized-CNN-from-scratch

Vectorized CNN implementation from scratch using only numpy

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mohadeseh-ghafoori/Residual-Networks

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mohadeseh-ghafoori/Semantic-Image-Segmentation-with-U-Net

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mohadeseh-ghafoori/Face-Recognition

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somjit101/MNIST-Classification-CNN

A simple study on the use of CNNs for a simple handwritten number image classification task using the Keras framework (with Tensorflow background).

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