94 citations · 217 across the 22 of their papers we have counts for
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ApHMM: Accelerating Profile Hidden Markov Models for Fast and Energy-Efficient Genome Analysis
Can Firtina, Kamlesh Pillai, Gurpreet S. Kalsi +10
Profile hidden Markov models (pHMMs) are widely employed in various bioinformatics applications to identify similarities between biological sequences, such as DNA or protein sequen…
SeGraM: A Universal Hardware Accelerator for Genomic Sequence-to-Graph and Sequence-to-Sequence Mapping
Damla Senol Cali, Konstantinos Kanellopoulos, Joel Lindegger +15
A critical step of genome sequence analysis is the mapping of sequenced DNA fragments (i.e., reads) collected from an individual to a known linear reference genome sequence (i.e.,…
Unsupervised Learning of Depth, Camera Pose and Optical Flow from Monocular Video
Dipan Mandal, Abhilash Jain
We propose DFPNet -- an unsupervised, joint learning system for monocular Depth, Optical Flow and egomotion (Camera Pose) estimation from monocular image sequences. Due to the natu…