Abstract: A method for identifying objects and determining their trajectories includes analyzing an image frame to identify an object, creating a bounding box around the object, filtering event data based on the position of the bounding box, and analyzing the filtered event data to determine a trajectory of the object. A system for identifying objects and determining trajectories of the objects.

Abstract: A method of reconstructing an image. The method includes performing panoptic segmentation of the image and performing instance segmentation of the image. The method further includes performing recurring image inpainting of the image. The recurring image inpainting of the image includes applying a first mask corresponding to the first object to the image, inpainting the first mask to form a partially reconstructed image, applying a second mask corresponding to the second object to the partially reconstructed image, and inpainting the second mask.

Abstract: There is provided a computer-implemented method of predicting a timeseries of time delays resulting from contention between tasks running in parallel on a multi-processor system using a trained Machine Learning based Task Contention Model, ML based TCM. The method comprises: executing a plurality of actual execution tasks on the multi-processor system in isolation, and for each task and during execution of the respective task, capturing a timeseries comprising a plurality of uWindows by capturing a plurality of snapshots, each snapshot comprising an array of performance monitoring counters, PMCs, since the previous snapshot, and the time since the previous snapshot. The method also includes inferring, from a time-agnostic ML based regressor, a predicted contention delay for the first uWindow of the timeseries when two or more of the plurality of actual execution tasks are executed on parallel on the multi-processor system given the first captured snapshot for each of the tasks to be completed in parallel.

Abstract: Disclosed is a method of training a language model to generate “microbenchmarks” in which the training data is specifically associated with certain microarchitecture characteristics that the “microbenchmarks” are designed for testing. Also disclosed are language models that have been trained in this manner, and the corresponding use thereof to generate “microbenchmarks”.

Abstract: An audio-visual pilot activity recognition system including one or more image collectors, one or more audio collectors, and a processor configured to collect at least one image signal from the one or more image collectors, collect at least one audio signal from the one of more audio collectors, and determine a pilot activity based on the collected at least one image signal and the collected at least one audio signal.

Abstract: A computer-implemented method of training a software agent for protecting a computer system comprises receiving performance monitoring counter (PMC) data, comprising data from one or more hardware performance monitoring counters (PMCs) of the computer system, and receiving an output from an anomaly detector that is arranged to detect anomalies in the computer system. State data, comprising at least the PMC data, is provided to the software agent which selects a security policy from a set of security policies in dependence upon the state data, and applies the selected security policy to the computer system. A reward function is evaluated to determine a reward value which depends on at least the output of the anomaly detector. The reward value is used to train the software agent using reinforcement learning for selecting security policies from the set of security policies.

Abstract: A method for operating an image segmentation system includes receiving image data from a sensor, detecting a vessel is present in the image data, extracting a region of interest, and classifying the image data based on the region of interest.

Abstract: A method of generating training data for training a Machine Learning based Task Contention Model, ML based TCM, to predict time delays resulting from contention between tasks running in parallel on a multi-processor system is provided herein. The method includes: executing a plurality of microbenchmarks, ?Benchmarks Bj, on the multi-processor system in isolation and measuring a number of resultant Performance Monitoring Counters, PMCs, over time to extract ideal characteristic footprints of each ?Benchmark when operating in isolation; performing a feature correlation analysis on the PMCs resulting from the plurality of ?Benchmarks to determine the degree of correlation between each resultant PMCs and the executed plurality of ?Benchmarks; selecting a number of PMCs based upon their degree of correlation between the plurality of ?Benchmarks to form a reduced PMC array.

Abstract: A method of allocating space on a spectrum on which information is transmitted, to information to be transmitted, the method comprising: identifying carrier frequencies and bandwidths of information being transmitted on the spectrum, determining an optimal carrier frequency and bandwidth for the information to be transmitted based on the carrier frequencies and bandwidths of information being transmitted on the spectrum; transmitting the information to be transmitted using modulation at the identified optimal carrier frequency and bandwidth.

Abstract: A method of analysing a spectrum on which information is transmitted, comprising: determining each different type of modulation used for transmitting the information across the spectrum, for each determined modulation, identifying its carrier frequency and its bandwidth, defining characteristics of usage of the spectrum in terms of the determined modulations and their corresponding carrier frequencies and bandwidths.