Abstract: An acoustic array system for anomaly detection is provided. The acoustic array system (100) performs a scan (or a progressive scan of frequencies) of a given volume by transmitting one or more signals, and receives one or more reflected signals from objects within the volume. The reflected signals are then amplified and converted to a set of digital signals. Features of the set of digital signals are extracted both in time and frequency domains. The acoustic array system (100) further performs a comparison of these set of digital extracted features with the reflected signals via machine learning techniques. Based on the comparison, the acoustic array system detects one or more anomalies.

Abstract: An acoustic array system for anomaly detection is provided. The acoustic array system (100) performs a scan (or a progressive scan of frequencies) of a given volume by transmitting one or more signals, and receives one or more reflected signals from objects within the volume. The reflected signals are then amplified and converted to a set of digital signals. Features of the set of digital signals are extracted both in time and frequency domains. The acoustic array system (100) further performs a comparison of these set of digital extracted features with the reflected signals via machine learning techniques. Based on the comparison, the acoustic array system detects one or more anomalies.

Abstract: Disclosed is a method and system for automatic algorithm selection for image processing. The invention discloses the method and system for automatically selecting the correct algorithm(s) for a varying requirement of the image for processing. The selection of algorithm is completely automatic and guided by a plurality of machine learning approaches. The system here is configured to pre-process plurality of images for creating a training data. Next, the test image is extracted, pre-processed and matched for assessing the best possible match of algorithm for processing.

Abstract: Disclosed is a method and system for automatic algorithm selection for image processing. The invention discloses the method and system for automatically selecting the correct algorithm(s) for a varying requirement of the image for processing. The selection of algorithm is completely automatic and guided by a plurality of machine learning approaches. The system here is configured to pre-process plurality of images for creating a training data. Next, the test image is extracted, pre-processed and matched for assessing the best possible match of algorithm for processing.