Description
SqueezeNet is a convolutional neural network that employs design strategies to reduce the number of parameters, notably with the use of fire modules that "squeeze" parameters using 1x1 convolutions.
Papers Using This Method
Detecting immune cells with label-free two-photon autofluorescence and deep learning2025-06-17Deploying and Evaluating Multiple Deep Learning Models on Edge Devices for Diabetic Retinopathy Detection2025-06-14SecONNds: Secure Outsourced Neural Network Inference on ImageNet2025-06-13Comparative Analysis of Lightweight Deep Learning Models for Memory-Constrained Devices2025-05-06Deepfake Detection with Optimized Hybrid Model: EAR Biometric Descriptor via Improved RCNN2025-03-16Comparison of Neural Models for X-ray Image Classification in COVID-19 Detection2025-01-08Improving the network traffic classification using the Packet Vision approach2024-12-26Evaluating Convolutional Neural Networks for COVID-19 classification in chest X-ray images2024-12-26RNC: Efficient RRAM-aware NAS and Compilation for DNNs on Resource-Constrained Edge Devices2024-09-27Evaluating Deep Learning Models for Breast Cancer Classification: A Comparative Study2024-08-29Deep Learning for Lung Disease Classification Using Transfer Learning and a Customized CNN Architecture with Attention2024-08-23Deep Network Pruning: A Comparative Study on CNNs in Face Recognition2024-05-28BanglaNum -- A Public Dataset for Bengali Digit Recognition from Speech2024-03-20Quantization Effects on Neural Networks Perception: How would quantization change the perceptual field of vision models?2024-03-15The Potential of Wearable Sensors for Assessing Patient Acuity in Intensive Care Unit (ICU)2023-11-03Multi-Transfer Learning Techniques for Detecting Auditory Brainstem Response2023-08-29SqueezerFaceNet: Reducing a Small Face Recognition CNN Even More Via Filter Pruning2023-07-20Modulation Classification Through Deep Learning Using Resolution Transformed Spectrograms2023-06-06PSDNet: Determination of Particle Size Distributions Using Synthetic Soil Images and Convolutional Neural Networks2023-03-07Use Cases for Time-Frequency Image Representations and Deep Learning Techniques for Improved Signal Classification2023-02-22