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Crowd Counting

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평가표: 13
보존된 평가 기록: 155

Crowd Counting is a task to count people in image. It is mainly used in real-life for automated public monitoring such as surveillance and traffic control. Different from object detection, Crowd Counting aims at recognizing arbitrarily sized targets in various situations including sparse and cluttering scenes at the same time.

Source: Deep Density-aware Count Regressor

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/ariangc/breinchallenge

Deep Residual Learning for Image Recognition

https://github.com/arnavdodiedo/DenseNet-Fashion-MNIST

Densely Connected Convolutional Networks

https://github.com/arnavdodiedo/DenseNet-MNIST

Densely Connected Convolutional Networks

https://github.com/arsalhuda24/SS_lstm

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

https://github.com/asad-62/IVP-DNN

Densely Connected Convolutional Networks

https://github.com/ashishpatel26/BrainMRI-Segmentation-Keras

Deep Residual Learning for Image Recognition

https://github.com/asprenger/keras_fc_densenet

Deep Residual Learning for Image Recognition

https://github.com/astoycos/Mini_Project2

Deep Residual Learning for Image Recognition

https://github.com/atapour/ransomware-classification

Densely Connected Convolutional Networks

https://github.com/aurelien-peden/Deep-Learning-paper-implementations

Deep Residual Learning for Image Recognition

https://github.com/avocardio/resnet_vs_convnext

Deep Residual Learning for Image Recognition

https://github.com/axmoyal/Steganalysis-with-CNN

Deep Residual Learning for Image Recognition

https://github.com/ayushmankumar7/SegNet---Tensorflow-2

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

https://github.com/ayushpatidar/PR1-DenseNet

Densely Connected Convolutional Networks

https://github.com/azima-fariha/DeepLearning_DenselyConnectedConvolutionalNetworks

Densely Connected Convolutional Networks

https://github.com/azy64/Deep-Learning

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

https://github.com/b8goal/PIRL-Residual-network

Deep Residual Learning for Image Recognition

https://github.com/bamos/densenet.pytorch

Densely Connected Convolutional Networks

https://github.com/barmayo/spatial_attention

Deep Residual Learning for Image Recognition

https://github.com/bclwan/MRI_Brain_Segmentation

Deep Residual Learning for Image Recognition

https://github.com/ben-davidson-6/fixup

Deep Residual Learning for Image Recognition

https://github.com/bentrevett/pytorch-image-classification

Deep Residual Learning for Image Recognition

https://github.com/bertrandlalo/deep_dog_breeds

Deep Residual Learning for Image Recognition

https://github.com/bethgelab/InDomainGeneralizationBenchmark

Deep Residual Learning for Image Recognition

https://github.com/bfortuner/pytorch_tiramisu

Densely Connected Convolutional Networks

https://github.com/bhaskar-gaur/DenseNet-Keras

Densely Connected Convolutional Networks

https://github.com/billlyzhaoyh/SegNetFromScratch

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

https://github.com/boris127/vehicle-detection

Deep Residual Learning for Image Recognition

https://github.com/bozliu/E2E-Keyword-Spotting

Densely Connected Convolutional Networks

https://github.com/brycexu/MR-Residual-Net

Deep Residual Learning for Image Recognition

https://github.com/burakalperen/Pytorch-Semantic-Segmentation

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

https://github.com/c1ph3rr/Deep-Residual-Learning-for-Image-Recognition

Deep Residual Learning for Image Recognition

https://github.com/calmisential/TensorFlow2.0_ResNet

Deep Residual Learning for Image Recognition

https://github.com/cameronchoi/r3det-copy

Deep Residual Learning for Image Recognition

https://github.com/canturan10/satellighte

Deep Residual Learning for Image Recognition

https://github.com/caojoshua/Plastic-Recyclability

Deep Residual Learning for Image Recognition

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