4 papers
Efficient Learned Image Compression Through Knowledge Distillation
Fabien Allemand, Attilio Fiandrotti, Sumanta Chaudhuri +1
Learned image compression sits at the intersection of machine learning and image processing. With advances in deep learning, neural network-based compression methods have emerged.…
Lightweight Embedded FPGA Deployment of Learned Image Compression with Knowledge Distillation and Hybrid Quantization
Alaa Mazouz, Sumanta Chaudhuri, Marco Cagnanzzo +3
Learnable Image Compression (LIC) has shown the potential to outperform standardized video codecs in RD efficiency, prompting the research for hardware-friendly implementations. Mo…
Security and Real-time FPGA integration for Learned Image Compression
Alaa Mazouz, Carl De Sousa Tria, Sumanta Chaudhuri +4
Learnable Image Compression (LIC) has proven capable of outperforming standardized video codecs in compression efficiency. However, achieving both real-time and secure LIC operatio…
WaterMAS: Sharpness-Aware Maximization for Neural Network Watermarking
Carl De Sousa Trias, Mihai Mitrea, Attilio Fiandrotti +3
Nowadays, deep neural networks are used for solving complex tasks in several critical applications and protecting both their integrity and intellectual property rights (IPR) has be…