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Found 7 papers, 4 papers with code
BinaryDM: Towards Accurate Binarization of Diffusion Model
With the advancement of diffusion models (DMs) and the substantially increased computational requirements, quantization emerges as a practical solution to obtain compact and efficient low-bit DMs.
Accurate LoRA-Finetuning Quantization of LLMs via Information Retention
This paper proposes a novel IR-QLoRA for pushing quantized LLMs with LoRA to be highly accurate through information retention.
BiFSMNv2: Pushing Binary Neural Networks for Keyword Spotting to Real-Network Performance
We highlight that benefiting from the compact architecture and optimized hardware kernel, BiFSMNv2 can achieve an impressive 25. 1x speedup and 20. 2x storage-saving on edge hardware.
ICIP 2022 Challenge on Parasitic Egg Detection and Classification in Microscopic Images: Dataset, Methods and Results
Manual examination of faecal smear samples to identify the existence of parasitic eggs is very time-consuming and can only be done by specialists.
BiFSMN: Binary Neural Network for Keyword Spotting
Then, to allow the instant and adaptive accuracy-efficiency trade-offs at runtime, we also propose a Thinnable Binarization Architecture to further liberate the acceleration potential of the binarized network from the topology perspective.
Unsupervised Image Fusion Using Deep Image Priors
The results are compared with state-of-the-art image fusion methods.
Multi-Camera Occlusion and Sudden-Appearance-Change Detection Using Hidden Markovian Chains
This paper was originally submitted to Xinova as a response to a Request for Invention (RFI) on new event monitoring methods.
