Results 31 to 40 of about 31,077 (302)
Statistical Pruning for Near Maximum Likelihood Detection of MIMO Systems [PDF]
, 2007 We show a statistical pruning approach for maximum likelihood (ML) detection of multiple-input multiple-output (MIMO) systems. We present a general pruning strategy for sphere decoder (SD), which can also be applied to any tree search algorithms. Our
Ho, Tracey +5 more
core +1 more source
A Recursive Ensemble Learning Approach With Noisy Labels or Unlabeled Data
IEEE Access, 2019 For many tasks, the successful application of deep learning relies on having large amounts of training data, labeled to a high standard. But much of the data in real-world applications suffer from label noise.
Yuchen Wang +3 more
doaj +1 more source
Deep Neural Network Compression with Filter Pruning [PDF]
, 2023 The rapid development of convolutional neural networks (CNNs) in computer vision tasks has inspired researchers to apply their potential to embedded or mobile devices.
Zhang, Shuo, Han, Jungong, Ni, Qiang
core
Coarse-Grained Pruning of Neural Network Models Based on Blocky Sparse Structure
Entropy, 2021 Deep neural networks may achieve excellent performance in many research fields. However, many deep neural network models are over-parameterized. The computation of weight matrices often consumes a lot of time, which requires plenty of computing resources.
Lan Huang +5 more
doaj +1 more source
Response of Riesling vines to training system and pruning strategy
, 2015 Riesling vines were subjected over a 3-year old period to four training systems (\u27flachbogen\u27; \u27pendelbogen\u27; low cordon; Moselle loop) in combination with two pruning strategies (30 + 10 balanced pruning; 25 nodes/m of row).
Reynolds, A. G.
core +1 more source
An automatic pruning method for SAR target detection based on multitask reinforcement learning
International Journal of Applied Earth Observations and GeoinformationIn recent years, research on synthetic aperture radar (SAR) target detection based on deep learning methods has made substantial progress in model accuracy.
Huiyao Wan +9 more
doaj +1 more source
Pruning Strategies for Backdoor Defense in LLMs
Proceedings of the 34th ACM International Conference on Information and Knowledge ManagementBackdoor attacks are a significant threat to the performance and integrity of pre-trained language models. Although such models are routinely fine-tuned for downstream NLP tasks, recent work shows they remain vulnerable to backdoor attacks that survive vanilla fine-tuning. These attacks are difficult to defend because end users typically lack knowledge
Santosh Chapagain +2 more
openaire +2 more sources
Leaftronics: Bio‐Fractal Scaffolds From Leaf Venation for Low‐Waste Electronics
Advanced Materials, EarlyView.“Leaftronics” transforms naturally evolved leaf venation into quasi‐fractal scaffolds for sustainable electronics. Polymer‐infiltrated leaf skeletons can be used to fabricate ultra‐smooth, reflow‐ and thin‐film‐compatible decomposable substrates, while making the same lignocellulose networks conducting results in flexible transparent electrodes.
Rakesh Rajendran Nair +3 more
wiley +1 more source
HortScience, 2023 Recently, some commercial apple growers have been adopting hedging as an alternative or supplement to hand-pruning. With increasing labor costs across the United States, alternatives to hand-pruning and current training systems are being considered.
Thiago Campbell +2 more
doaj +1 more source
Connected operators based on region-tree pruning strategies [PDF]
Proceedings 15th International Conference on Pattern Recognition. ICPR-2000, 2002 This paper discusses region-based representations useful to create connected operators. The filtering approach involves three steps: 1) a region tree representation of the input image is constructed; 2) the simplification is obtained by pruning the tree; and 3) and output image is constructed from the pruned tree. The paper focuses in particular on the
Salembier Clairon, Philippe Jean +1 more
openaire +2 more sources