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Mohammed Shoaib
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2020 – today
- 2024
- [i1]Matilda Beinat, Julian Beinat, Mohammed Shoaib, Jorge Gomez Magenti:
Machine Learning to Promote Translational Research: Predicting Patent and Clinical Trial Inclusion in Dementia Research. CoRR abs/2401.05145 (2024)
2010 – 2019
- 2017
- [j7]Mark Gottscho, Mohammed Shoaib, Sriram Govindan, Bikash Sharma, Di Wang, Puneet Gupta
:
Measuring the Impact of Memory Errors on Application Performance. IEEE Comput. Archit. Lett. 16(1): 51-55 (2017) - 2016
- [c13]Xin Zhan, Mohammed Shoaib, Sherief Reda:
Creating Soft Heterogeneity in Clusters Through Firmware Re-configuration. CCGrid 2016: 540-549 - [c12]Mark Gottscho, Sriram Govindan, Bikash Sharma, Mohammed Shoaib, Puneet Gupta
:
X-Mem: A cross-platform and extensible memory characterization tool for the cloud. ISPASS 2016: 263-273 - 2015
- [j6]Soham Jayesh Desai
, Mohammed Shoaib, Arijit Raychowdhury:
An Ultra-Low Power, "Always-On" Camera Front-End for Posture Detection in Body Worn Cameras Using Restricted Boltzman Machines. IEEE Trans. Multi Scale Comput. Syst. 1(4): 187-194 (2015) - [j5]Mohammed Shoaib, Niraj K. Jha, Naveen Verma:
Signal Processing With Direct Computations on Compressively Sensed Data. IEEE Trans. Very Large Scale Integr. Syst. 23(1): 30-43 (2015) - [c11]Vahid Behravan, Neil E. Glover, Rutger Farry, Patrick Yin Chiang, Mohammed Shoaib:
Rate-adaptive compressed-sensing and sparsity variance of biomedical signals. BSN 2015: 1-6 - [c10]Vahid Behravan, Shuo Li, Neil E. Glover, Chia-Hung Chen, Mohammed Shoaib, Gabor C. Temes, Patrick Yin Chiang:
A compressed-sensing sensor-on-chip incorporating statistics collection to improve reconstruction performance. CICC 2015: 1-4 - [c9]Swagath Venkataramani, Anand Raghunathan
, Jie Liu, Mohammed Shoaib:
Scalable-effort classifiers for energy-efficient machine learning. DAC 2015: 67:1-67:6 - [c8]Swagath Venkataramani, Victor Bahl, Xian-Sheng Hua, Jie Liu, Jin Li, Matthai Philipose, Bodhi Priyantha, Mohammed Shoaib:
SAPPHIRE: an always-on context-aware computer vision system for portable devices. DATE 2015: 1491-1496 - [p1]Mohammed Shoaib, Swagath Venkataramani, Xian-Sheng Hua, Jie Liu, Jin Li:
Exploiting On-Device Image Classification for Energy Efficiency in Ambient-Aware Systems. Mobile Cloud Visual Media Computing 2015: 167-199 - 2014
- [j4]Mohammed Shoaib, Kyong-Ho Lee, Niraj K. Jha, Naveen Verma:
A 0.6-107 µW Energy-Scalable Processor for Directly Analyzing Compressively-Sensed EEG. IEEE Trans. Circuits Syst. I Regul. Pap. 61-I(4): 1105-1118 (2014) - [c7]Mohammed Shoaib, Jie Liu, Matthai Philipose:
Energy scaling in multi-tiered sensing systems through compressive sensing. CICC 2014: 1-8 - 2013
- [j3]Mohammed Shoaib, Niraj K. Jha, Naveen Verma:
Algorithm-Driven Architectural Design Space Exploration of Domain-Specific Medical-Sensor Processors. IEEE Trans. Very Large Scale Integr. Syst. 21(10): 1849-1862 (2013) - 2012
- [c6]Mohammed Shoaib, Niraj K. Jha, Naveen Verma:
A compressed-domain processor for seizure detection to simultaneously reduce computation and communication energy. CICC 2012: 1-4 - [c5]Mohammed Shoaib, Gene Marsh, Harinath Garudadri, Somdeb Majumdar:
A closed-loop system for artifact mitigation in ambulatory electrocardiogram monitoring. DATE 2012: 431-436 - [c4]Mohammed Shoaib, Niraj K. Jha, Naveen Verma:
Enabling advanced inference on sensor nodes through direct use of compressively-sensed signals. DATE 2012: 437-442 - 2011
- [c3]Mohammed Shoaib, Niraj K. Jha, Naveen Verma:
A low-energy computation platform for data-driven biomedical monitoring algorithms. DAC 2011: 591-596 - 2010
- [c2]Guotong Feng, Mohammed Shoaib, Edward L. Schwartz, M. Dirk Robinson:
Low-cost space-varying FIR filter architecture for computational imaging systems. Digital Photography 2010: 75370
2000 – 2009
- 2006
- [c1]Siew Kei Lam
, Mohammed Shoaib, Thambipillai Srikanthan:
Modeling Arbitrator Delay-Area Dependencies in Customizable Instruction Set Processors. DELTA 2006: 237-242 - 2004
- [j2]Mohammed Shoaib, Andrew S. Lowe
, Steven C. R. Williams
:
Imaging localised dynamic changes in the nucleus accumbens following nicotine withdrawal in rats. NeuroImage 22(2): 847-854 (2004) - 2002
- [j1]Andrew S. Lowe
, Steven C. R. Williams
, Mark R. Symms, Ian P. Stolerman, Mohammed Shoaib:
Functional Magnetic Resonance Neuroimaging of Drug Dependence: Naloxone-Precipitated Morphine Withdrawal. NeuroImage 17(2): 902-910 (2002)
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last updated on 2024-04-25 05:45 CEST by the dblp team
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