Abstract: Methods and systems are provided for detecting a defect in a solar panel. The method includes initially imaging, via an infrared camera, a group of solar panels. Then, identifying, via a computer system configured for solar panel defect detection, the individual solar panels in the group of solar panels. Finally, identifying, via evaluation of an infrared image obtained by the infrared camera, a defect in at least one of the group of solar panels.

Abstract: Methods and systems are provided for detecting a defect in a solar panel. The method includes initially imaging, via an infrared camera, a group of solar panels. Then, identifying, via a computer system configured for solar panel defect detection, the individual solar panels in the group of solar panels. Finally, identifying, via evaluation of an infrared image obtained by the infrared camera, a defect in at least one of the group of solar panels.

Abstract: Methods and systems are provided for detecting a defect in a solar panel. The method includes initially imaging, via an infrared camera, a group of solar panels. Then, identifying, via a computer system configured for solar panel defect detection, the individual solar panels in the group of solar panels. Finally, identifying, via evaluation of an infrared image obtained by the infrared camera, a defect in at least one of the group of solar panels.

Abstract: Methods and systems are provided for detecting a defect in a solar panel. The method includes initially imaging, via an infrared camera, a group of solar panels. Then, identifying, via a computer system configured for solar panel defect detection, the individual solar panels in the group of solar panels. Finally, identifying, via evaluation of an infrared image obtained by the infrared camera, a defect in at least one of the group of solar panels.

Abstract: In a communication network (20), a video encoder/decoder system (114) and an encoding method (150) facilitate transmission of video frames (116) over multiple low-data-rate channels (46). Frame data (204) is generated for each video frame (116). The frame data (204) is transformed (172) to obtain transform coefficients (212), which are assembled (174) into quadtrees (216) and separately coded (178). In addition, motion vectors (166) are split into coding blocks (188) and separately coded (190). The quadtrees (126) and the motion vectors (166) are independently distributed among the multiple channels (46) for transmission. A decoding method (360) facilitates error resilient reception of transform coefficient packets (222) and motion vector packets (244) so that lost transform coefficients (374) and/or lost motion vectors (384) can be estimated at a receiving video encoder/decoder system (114) to reconstruct a received video frames 144.

Abstract: In a wireless communication system (20) configured for default communication of subsectional signals of a first transmit signal (72/73) over multiple wireless channels (46), a signal selector (82) and method (138) detect an intent to convey a voice signal (86) over one of the wireless channels (46) from a handset (58). The signal selector (82) and method (138) prevent communication of one of the subsectional signals (72A) over the wireless channel (46) for a predetermined interval, and enable a transmission attempt of the voice signal (86). When a complete dialed digits sequence is detected within the time interval, the handset (58) is enabled to utilize the wireless channel. However, when a transmission attempt of the voice signal (86) is unsuccessful or when transmission of the voice signal (86) terminates, the signal selector (82) and method (138) restore default communication of subsectional signals of the first transmit signal (72/73).

Abstract: A knowledge-based hierarchical method for detecting regions of interests (ROIs) uses prior knowledge of the targets and the image resolution in detecting ROIs. The result produces ROIs that contain only one target that is completely enclosed within the ROI. The detected ROI can conform to the shape of the target even if the target is of irregular shape. Furthermore, the method works well with images that contain connected targets or targets broken into pieces. The method is not sensitive to contrast levels and is robust to noise. Thus, this method effectively detects ROIs in common real world imagery that has a low resolution without costly processing while providing fast and robust results.

Abstract: In a communication network (20), a video encoder/decoder system (114) and an encoding method (150) facilitate transmission of video frames (116) over multiple low-data-rate channels (46). Frame data (204) is generated for each video frame (116). The frame data (204) is transformed (172) to obtain transform coefficients (212), which are assembled (174) into quadtrees (216) and separately coded (178). In addition, motion vectors (166) are split into coding blocks (188) and separately coded (190). The quadtrees (126) and the motion vectors (166) are independently distributed among the multiple channels (46) for transmission. A decoding method (360) facilitates error resilient reception of transform coefficient packets (222) and motion vector packets (244) so that lost transform coefficients (374) and/or lost motion vectors (384) can be estimated at a receiving video encoder/decoder system (114) to reconstruct a received video frames 144.

Abstract: A method of utilizing low-data-rate wireless channels (46) in a satellite-based wireless communication network (20) detects a transmit signal (64) and determines a data type (120, 122, 124) for the transmit signal (64). A quantity of the wireless channels (46) are assigned for transmission of the transmit signal (64) in response to the data type (120, 122, 124). An inverse multiplexing system (50) selectively splits the transmit signal (64) into multiple subsectional signals for transmission over separate wireless channels (46) to facilitate the transmission of large data files and real-time video imagery over the low-data-rate wireless channels (46).

Abstract: A knowledge-based hierarchical method for detecting regions of interests (ROIs) uses prior knowledge of the targets and the image resolution in detecting ROIs. The result produces ROIs that contain only one target that is completely enclosed within the ROI. The detected ROI can conform to the shape of the target even if the target is of irregular shape. Furthermore, the method works well with images that contain connected targets or targets broken into pieces. The method is not sensitive to contrast levels and is robust to noise. Thus, this method effectively detects ROIs in common real world imagery that has a low resolution without costly processing while providing fast and robust results.