Abstract: A wideband-tunable radio frequency (RF) receiver having a tunable RF bandpass filter (RF BPF) and passive mixer-first receiver (PMF-Rx) is disclosed. The tunable RF BPF and PMF-Rx operate synergistically, exploiting the intrinsic impedance translation property of the PMF-Rx, to suppress out-of-band interferers as well as in-band interferers at the receiver front end and thereby enhance the receiver's signal-to-noise ratio and overall dynamic range. In one embodiment of the invention the tunable RF BPF and PMF-Rx are independently tunable and afford the receiver the ability to reject or suppress interferers that might not otherwise be able to be rejected or suppressed.

Abstract: A neural network is trained using transfer learning to analyze medical image data, including 2D, 3D, and 4D images and models. Where the target medical image data is associated with a species or problem class for which there is not sufficient labeled data available for training, the system may create enhanced training datasets by selecting labeled data from other species, and/or labeled data from different problem classes. During training and analysis, image data is chunked into portions that are small enough to obfuscate the species source, while being large enough to preserve meaningful context related to the problem class (e.g., the image portion is small enough that it cannot be determined whether it is from a human or canine, but abnormal liver tissues are still identifiable). A trained checkpoint may then be used to provide automated analysis and heat mapping of input images via a cloud platform or other application.

Abstract: A neural network is trained using transfer learning to analyze medical image data, including 2D, 3D, and 4D images and models. Where the target medical image data is associated with a species or problem class for which there is not sufficient labeled data available for training, the system may create enhanced training datasets by selecting labeled data from other species, and/or labeled data from different problem classes. During training and analysis, image data is chunked into portions that are small enough to obfuscate the species source, while being large enough to preserve meaningful context related to the problem class (e.g., the image portion is small enough that it can't be determined whether it is from a human or canine, but abnormal liver tissues are still identifiable). A trained checkpoint may then be used to provide automated analysis and heat mapping of input images via a cloud platform or other application.

Abstract: A wideband-tunable radio frequency (RF) receiver having a tunable RF bandpass filter (RF BPF) and passive mixer-first receiver (PMF-Rx) is disclosed. The tunable RF BPF and PMF-Rx operate synergistically, exploiting the intrinsic impedance translation property of the PMF-Rx, to suppress out-of-band interferers as well as in-band interferers at the receiver front end and thereby enhance the receiver's signal-to-noise ratio and overall dynamic range. In one embodiment of the invention the tunable RF BPF and PMF-Rx are independently tunable and afford the receiver the ability to reject or suppress interferers that might not otherwise be able to be rejected or suppressed.

Abstract: A neural network is trained using transfer learning to analyze medical image data, including 2D, 3D, and 4D images and models. Where the target medical image data is associated with a species or problem class for which there is not sufficient labeled data available for training, the system may create enhanced training datasets by selecting labeled data from other species, and/or labeled data from different problem classes. During training and analysis, image data is chunked into portions that are small enough to obfuscate the species source, while being large enough to preserve meaningful context related to the problem class (e.g., the image portion is small enough that it can't be determined whether it is from a human or canine, but abnormal liver tissues are still identifiable). A trained checkpoint may then be used to provide automated analysis and heat mapping of input images via a cloud platform or other application.

Abstract: A neural network is trained using transfer learning to analyze medical image data, including 2D, 3D, and 4D images and models. Where the target medical image data is associated with a species or problem class for which there is not sufficient labeled data available for training, the system may create enhanced training datasets by selecting labeled data from other species, and/or labeled data from different problem classes. During training and analysis, image data is chunked into portions that are small enough to obfuscate the species source, while being large enough to preserve meaningful context related to the problem class (e.g., the image portion is small enough that it can't be determined whether it is from a human or canine, but abnormal liver tissues are still identifiable). A trained checkpoint may then be used to provide automated analysis and heat mapping of input images via a cloud platform or other application.

Abstract: A neural network is trained using transfer learning to analyze medical image data, including 2D, 3D, and 4D images and models. Where the target medical image data is associated with a species or problem class for which there is not sufficient labeled data available for training, the system may create enhanced training datasets by selecting labeled data from other species, and/or labeled data from different problem classes. During training and analysis, image data is chunked into portions that are small enough to obfuscate the species source, while being large enough to preserve meaningful context related to the problem class (e.g., the image portion is small enough that it can't be determined whether it is from a human or canine, but abnormal liver tissues are still identifiable). A trained checkpoint may then be used to provide automated analysis and heat mapping of input images via a cloud platform or other application.

Abstract: A shaped charge casing 1 designed to be nested to reduce overall volume, which benefits storage or carriage. A lid portion 5 is connected at 8 to a body portion 9 by means of a screw thread. A shaped charge liner 12 can be positioned onto lip 11. The lid portion 5 and body portion 9 can be separated to allow filling or unpacking of explosive material.

Abstract: A shaped charge casing 1 designed to be nested to reduce overall volume, which benefits storage or carriage. A lid portion 5 is connected at 8 to a body portion 9 by means of a screw thread. A shaped charge liner 12 can be positioned onto lip 11. The lid portion 5 and body portion 9 can be separated to allow filling or unpacking of explosive material.