Results 231 to 240 of about 308,238 (274)

High performance GPU implementation of KNN algorithm: A review. [PDF]

MethodsX
Bidye P, Borkar P, Rakesh N.
europepmc   +1 more source

Autonomous Robotic Colonoscopy: A Supervised Learning Approach for Enhanced Navigation and Collision Detection

Advanced Intelligent Systems, EarlyView.
A novel autonomous robotic colonoscopy is introduced through supervised learning approaches. The proposed system consists of 3 degrees of freedom motorized colonoscope with an integrated navigation module that can infer a target steering point and collision probability.
Bohyun Hwang, Dae Kyung Sohn, Seonggun Joe, Byungkyu Kim   +3 more
wiley   +1 more source

ProteinDJ: A high-performance and modular protein design pipeline. [PDF]

Protein Sci
Silke D, Iskander J, Pan J, Thompson AP, Papenfuss AT, Lucet IS, Hardy JM.   +6 more
europepmc   +1 more source

Workflow Analysis for CGH Generation with Speckle Reduction and Occlusion Culling Using GPU Acceleration. [PDF]

Sensors (Basel)
Serón FJ, Blesa A, Sanz D.
europepmc   +1 more source

ArtiDock: Accurate Machine Learning Approach to Protein-Ligand Docking Optimized for High-Throughput Virtual Screening. [PDF]

J Chem Inf Model
Voitsitskyi T, Koleiev I, Stratiichuk R, Kot O, Kyrylenko R, Savchenko I, Husak V, Yesylevskyy S, Starosyla S, Nafiiev A.   +9 more
europepmc   +1 more source

Inverse Lithography Technology (ILT) Under Chip Manufacture Context. [PDF]

Micromachines (Basel)
Meng X, Chen C, Ni J.
europepmc   +1 more source

FM-DLM: A new method for image classification based on the fusion of multi-level deep learning models. [PDF]

PLoS One
Jin G, Li H, Du H, Song Q.
europepmc   +1 more source

Coil Sketching for Fast and Efficient 4D Lung MRI Reconstruction. [PDF]

Magn Reson Med
Plummer JW, Daudé P, Tsakirellis A, Taylor J, Moss J, Ramasawmy R, Javed A, Campbell-Washburn AE.   +7 more
europepmc   +1 more source

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DO-GPU: Domain Optimizable Soft GPUs

2021 31st International Conference on Field-Programmable Logic and Applications (FPL), 2021
”Soft” GPUs are overlays that implement GPGPU-like data parallel processor architectures in FPGA logic to make FPGAs as software-programmable as ”hard” GPGPUs. Unlike hard GPUs, soft GPU architectures can be specialized to further improve efficiency by leveraging FPGA’s flexibility.
Rui Ma, Jia-Ching Hsu, Tian Tan, Eriko Nurvitadhi, Rajesh Vivekanandham, Aravind Dasu, Martin Langhammer, Derek Chiou   +7 more
openaire   +1 more source