John Warburton

In what the service said is a further response to rising crime around two West Sussex villages, Sussex Police have arrested a total of 14 people.

A 34 year old roofer from Horsham has been jailed for a lengthy violent attack on a woman that caused her to black out several times.

Brighton's local authority together with its bus company said late this afternoon that North Street, in the city centre, has now reopened.

Weekend closures on the A27 eastbound between Lancing Manor Roundabout and the Adur junction (Shoreham) started on Friday night.

The University of Brighton Design Archives is set to receive £315,000 from the Research England Museum, Galleries and Collections Fund.

Tim Loughton, the Conservative East Worthing and Shoreham MP since 1997, has announced he won't compete for the seat in the forthcoming general election.

Family-run textile brand Rucomfy have launched a new collection of weatherproof cushions which will add colour and pattern to outdoor furniture this summer.

Leeds-based SlatWall specialists Naturewall have launched a trio of new collections designed to make it even easier for homeowners to add character and personality to their interiors.

This August Bank Holiday weekend in Sussex, “Into the Wild” is celebrating a decade of friendship, workshops, wildcrafts and music, as it continues to make its claim to be the UK’s premier nature and wellbeing festival.

Boxing punch type classification and kinematic analysis are essential for coaches and athletes, providing critical insights into punch variety and effectiveness, which are vital for performance improvement. Existing methods for punch recognition and classification typically rely on wearable sensor data or video data; however, no fully automated system currently exists. While coaches prefer video-based analysis for its ability to easily visualize punch action errors and refine technique, video-based classification suffers from lower accuracy compared to sensor-based methods due to limitations such as motion blur. Current classification approaches typically employ supervised learning, requiring experts to annotate 70–80% of the data for model training. However, the high sampling frequency of sensor data makes this process time-consuming and challenging, leading to potential fatigue and an increased risk of inconsistent annotations by domain experts. This paper proposes a novel multimodal approach that integrates wearable sensor data and video data for automatic punch recognition and classification. The method also includes automatic segmentation of punch videos, which improves classification accuracy by utilizing both data sources. To reduce labeling effort, we apply a Query by Committee-based active learning technique, significantly decreasing the required labeling effort by one-sixth. Using only 15% of the typical labeling effort, our system achieves 91.41% accuracy for rear-hand punch recognition, 91.91% for lead-hand punch recognition, and 92.33% and 94.56% for punch classification, respectively. This Smart Boxer system aims to enhance punch analytics in boxing, providing valuable insights to improve training, optimize performance, and increase fan engagement with the sport.